Qnum Analytics is a B2B SaaS smart inventory shrinkage solutions provider for the dry bulk industrial sector.
The company leverages data science powered technology to deliver end-to-end inventory control in order to maximise the inventory ROI for clients in the mining, manufacturing, and distribution sectors.
The core challenge in the dry bulk industry is an inability to have access to an accurate account of physical inventory levels in real-time. In the current state demand and supply planning decisions are made referencing incorrect inventory records which results in pain points that are negatively impacting profit margins; unnecessary stock write-offs, lost sales due to stock-outs, and excess cash tied up in inventory due to overstocking.
Systems and technologies employed (ERP, scanners, loadcells, order tracking, and weighing systems) currently do not consolidate the inventory information which opens blind spots and limits access to reliable insights. This creates significant discrepancies between the financial records and physical stock on the floor.
The Qnum Analytics team is driven by a mission to help clients isolate, classify and control root causes of inventory shrinkage losses by applying our disruptive AI technology that uniquely adapts to each client operation (without the hard coding).
The business also seeks to unlock capabilities that optimise supply and demand planning to improve profit margins.